Beamforming design with fully connected analog beamformer using deep learning-Reference-Cited by-同舟云学术

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Beamforming design with fully connected analog beamformer using deep learning

Published:2022-02-03 Issue:7 Volume:35 Page:
ISSN:1074-5351
Container-title:International Journal of Communication Systems
language:en
Short-container-title:Int J Communication

Author:

P. Jeyakumar¹^ORCID,M. Tharanitaran N.²,E. Malar³,P. Muthuchidambaranathan⁴

Affiliation:

1. Department of Electronics and Communication Engineering M.Kumarasamy College of Engineering Karur Tamilnadu India

2. Department of Applied Mathematics and Computational Sciences PSG College of Technology Coimbatore Tamilnadu India

3. Department of Electrical and Electronics Engineering PSG Institute of Technology and Applied Research Coimbatore Tamilnadu India

4. Department of Electronics and Communication Engineering National Institute of Technology Tiruchirappalli Tamilnadu India

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/dac.5109

Reference21 articles.

1. Spatially Sparse Precoding in Millimeter Wave MIMO Systems

2. Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems

3. Hybrid Beamforming for Millimeter Wave Systems Using the MMSE Criterion

4. Alternating Minimization Algorithms for Hybrid Precoding in Millimeter Wave MIMO Systems

5. Hybrid Digital and Analog Beamforming Design for Large-Scale Antenna Arrays

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